"Master data science with our course. Unlock the power of data to make informed decisions and drive innovation in a data-driven world."
Course Content :
1. Introduction to Data Science
• Understanding the role of data science in various industries
• Overview of data science tools and methodologies
2. Data Collection and Cleaning
• Techniques for gathering and preparing data for analysis
• Dealing with missing values and outliers
3. Exploratory Data Analysis (EDA)
• Visualizing and summarizing data to gain insights
• Identifying patterns and trends
4. Statistical Analysis
• Applying statistical techniques for hypothesis testing
• Inferential statistics and probability concepts
5. Machine Learning Fundamentals
• Introduction to machine learning algorithms
• Supervised and unsupervised learning techniques
6. Data Modeling and Feature Engineering
• Creating and optimizing predictive models
•Feature selection and engineering for model performance
7. Data Visualization
• Communicating insights through effective data visualization
• Using tools like Matplotlib, Seaborn, or Tableau
8. Big Data and Distributed Computing
• Handling large datasets with technologies like Hadoop and Spark
• Distributed computing and parallel processing
9. Natural Language Processing (NLP)
• Understanding and processing human language data
• Text mining and sentiment analysis
10 . Capstone Project and Real-world Applications
• Applying data science skills to a real-world project
• Exploring data science applications in various domains
This course content covers the fundamentals of data science, from data collection to analysis and modeling, preparing students to extract meaningful insights and make data-driven decisions.
Education; 12th | Age: 15 Years
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